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Inorganic polyphosphate, a linear polymer of orthophosphate residues linked by phosphoanhydride bonds, occurs in all three domains of life and plays a diverse and prominent role in metabolism and cellular regulation. While the polyphosphate metabolism and its physiological significance have been well studied in bacteria and eukaryotes including human, there are only few studies in archaea available so far. In Crenarchaeota including members of Sulfolobaceae , the presence of polyphosphate and degradation via exopolyphosphatase has been reported and there is some evidence for a functional role in metal ion chelation, biofilm formation, adhesion and motility, however, the nature of the crenarchaeal polyphosphate kinase is still unknown. Here we used the crenarchaeal model organism Sulfolobus acidocaldarius to study the enzymes involved in polyphosphate synthesis. The two genes annotated as thymidylate kinase ( saci_2019 and saci_2020 ), localized downstream of the exopolyphosphatase, were identified as the missing polyphosphate kinase in S. acidocaldarius ( Sa PPK3). Thymidylate kinase activity was confirmed for Saci_0893. Notably Saci_2020 showed no polyphosphate kinase activity on its own but served as regulatory subunit (rPPK3) and was able to enhance polyphosphate kinase activity of the catalytically active subunit Saci_2019 (cPPK3). Heteromeric polyphosphate kinase activity is reversible and shows a clear preference for polyP-dependent nucleotide kinase activity, i.e. polyP-dependent formation of ATP from ADP (12.4 U/mg) and to a lower extent of GDP to GTP whereas AMP does not serve as substrate. PPK activity in the direction of ATP-dependent polyP synthesis is rather low (0.25 U/mg); GTP was not used as phosphoryl donor. A combined experimental modelling approach using quantitative 31 P NMR allowed to follow the reversible enzyme reaction for both ATP and polyP synthesis. PolyP synthesis was only observed when the ATP/ADP ratio was kept high, using an ATP recycling system. In absence of such a recycling system, all incubations with polyP and PPK would reach an equilibrium state with an ATP/ADP ratio between 3 and 4, independent of the initial conditions. Structural and sequence comparisons as well as phylogenetic analysis reveal that the S. acidocaldarius PPK is a member of a new PPK family, named PPK3, within the thymidylate kinase family of the P-loop kinase superfamily, clearly separated from PPK2. Our studies show that polyP, in addition to its function as phosphate storage, has a special importance for the energy homeostasis of S. acidocaldarius and due to its reversibility serves as energy buffer under low energy charge enabling a quick response to changes in cellular demand.

Glycolytic oscillations have been studied for well over 60 years, but aspects of their function, and mechanisms of regulation and synchronisation remain unclear. Glycolysis is amenable to mechanistic mathematical modelling, as its components have been well characterised, and the system can be studied at many organisational levels: in vitro reconstituted enzymes, cell free extracts, individual cells, and cell populations. In recent years, the emergence of individual cell analysis has opened new ways of studying this intriguing system., (© 2024 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.)

Aldo-keto reductase 1C3 (AKR1C3) is a key enzyme in the activation of both classic and 11-oxygenated androgens. In adipose tissue, AKR1C3 is co-expressed with 11β-hydroxysteroid dehydrogenase type 1 (HSD11B1), which catalyzes not only the local activation of glucocorticoids but also the inactivation of 11-oxygenated androgens, and thus has the potential to counteract AKR1C3. Using a combination of in vitro assays and in silico modeling we show that HSD11B1 attenuates the biosynthesis of the potent 11-oxygenated androgen, 11-ketotestosterone (11KT), by AKR1C3. Employing ex vivo incubations of human female adipose tissue samples we show that inhibition of HSD11B1 results in the increased peripheral biosynthesis of 11KT. Moreover, circulating 11KT increased 2-3 fold in individuals with type 2 diabetes after receiving the selective oral HSD11B1 inhibitor AZD4017 for 35 days, thus confirming that HSD11B1 inhibition results in systemic increases in 11KT concentrations. Our findings show that HSD11B1 protects against excess 11KT production by adipose tissue, a finding of particular significance when considering the evidence for adverse metabolic effects of androgens in women. Therefore, when targeting glucocorticoid activation by HSD11B1 inhibitor treatment in women, the consequently increased generation of 11KT may offset beneficial effects of decreased glucocorticoid activation., (© 2024 The Authors. The FASEB Journal published by Wiley Periodicals LLC on behalf of Federation of American Societies for Experimental Biology.)

By analysing a large set of models obtained from the JWS Online and Biomodels databases, we tested to what extent the disequilibrium ratio can be used as an estimator for the flux control of a reaction, a discussion point that was already raised by Kacser and Burns, and Heinrich and Rapoport in their seminal MCA manuscripts. Whereas no functional relation was observed, the disequilibrium ratio can be used as an estimator for the maximal flux control of a reaction step. We extended the original analysis of the relationship by incorporating the overall pathway disequilibrium ratio in the expression, which made it possible to make explicit expressions for flux control coefficients., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Upon infection by the malaria parasite Plasmodium falciparum, the glycolytic rate of a red blood cell increases up to 100-fold, possibly contributing to lactic acidosis and hypoglycemia in patients with severe malaria. This dramatic increase in glucose uptake and metabolism was correctly predicted by a newly constructed detailed enzyme kinetic model of glucose metabolism in the trophozoite-infected red blood cell. Subsequently, we expanded the model to simulate an infected red blood cell culture, including the different asexual blood-stage forms of the malaria parasite. The model simulations were in good agreement with experimental data, for which the measured parasitic volume was an important parameter. Upon further analysis of the model, we identified glucose transport as a drug target that would specifically affect infected red blood cells, which was confirmed experimentally with inhibitor titrations. This model can be a first step in constructing a whole-body model for glucose metabolism in malaria patients to evaluate the contribution of the parasite's metabolism to the disease state., Competing Interests: Conflict of interest The authors declare that they have no conflicts of interest with the contents of this article., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

The glycolytic flux, and in particular lactate production, is strongly increased in cancer cells compared to normal cells, a characteristic often referred to as aerobic glycolysis or the Warburg effect. This makes the glycolytic pathway a potential drug target, in particular if the flux control distribution in the pathway has shifted due to the metabolic reprogramming in cancer cells. The flux response of a drug is dependent on both the sensitivity of the target to the drug and the flux control of the target, and both these characteristics can be exploited to obtain selectivity for cancer cells. Traditionally drug development programs have focused on selective sensitivity of the drug, not necessarily focussing on the flux control of the target. We determined the flux control of two steps that have been suggested to have high control in cancer cells, using two inhibitors, iodoacetic acid and 3-bromopyruvate, and measured a flux control of the glyceraldehyde 3-phosphate dehydrogenase close to zero, while the hexokinase holds 50% of all flux control in glycolysis in an invasive cancer cell line MDA-mb-231., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Tryptocidine C (TpcC), a Trp-rich cyclodecapeptide is a minor constituent in the antibiotic tyrothricin complex from Brevibacillus parabrevis. TpcC possesses a high tendency to oligomerise in aqueous solutions and dried TpcC forms distinct self-assembled nanoparticles. High-resolution scanning electron microscopy revealed the influence of different ethanol:water solvent systems on TpcC self-assembly, with the TpcC, dried from a high concentration in 15% ethanol, primarily assembling into small nanospheres with 24.3 nm diameter and 0.05 polydispersity. TpcC at 16 μM, near its CMC, formed a variety of structures such as small nanospheres, large dense nanospheroids and facetted 3-D-crystals, as well as sheets and coarse carpet-like structures which depended on ethanol concentration. Drying 16 μM TpcC from 75% ethanol resulted in highly facetted 3-D crystals, as well as small nanospheres, while those in 10% ethanol preparation had less defined facets. Drying from 20 to 50% ethanol led to polymorphic architectures with a few defined nanospheroids and various small nanoparticles, imbedded in carpet- and sheet-like structures. These polymorphic surface morphologies correlated with maintenance of fluorescence properties and the surface-derived antibacterial activity against Staphylococcus aureus over time, while there was a significant change in fluorescence and loss in activity in the 10% and 75% preparations where 3-D crystals were observed. This indicated that TpcC oligomerisation in solutions with 20-50% ethanol leads to metastable structures with a high propensity for release of antimicrobial moieties, while those leading to crystallisation limit active moieties release. TpcC nano-assemblies can find application in antimicrobial coatings, surface disinfectants, food packaging and wound healing materials., Competing Interests: Declaration of competing interest The authors declare that there is no reasonable conflict of interest and that this was an independent study without any interference, guidance, or regulation by commercial entities., (Copyright © 2022 Elsevier B.V. and Société Française de Biochimie et Biologie Moléculaire (SFBBM). All rights reserved.)

Background: The fidelity and reliability of disease model predictions depend on accurate and precise descriptions of processes and determination of parameters. Various models exist to describe within-host dynamics during malaria infection but there is a shortage of clinical data that can be used to quantitatively validate them and establish confidence in their predictions. In addition, model parameters often contain a degree of uncertainty and show variations between individuals, potentially undermining the reliability of model predictions. In this study models were reproduced and analysed by means of robustness, uncertainty, local sensitivity and local sensitivity robustness analysis to establish confidence in their predictions., Results: Components of the immune system are responsible for the most uncertainty in model outputs, while disease associated variables showed the greatest sensitivity for these components. All models showed a comparable degree of robustness but displayed different ranges in their predictions. In these different ranges, sensitivities were well-preserved in three of the four models., Conclusion: Analyses of the effects of parameter variations in models can provide a comparative tool for the evaluation of model predictions. In addition, it can assist in uncovering model weak points and, in the case of disease models, be used to identify possible points for therapeutic intervention., (© 2021. The Author(s).)

This study demonstrates the application of a mathematical steroidogenic model, constructed with individual in vitro enzyme characterisations, to simulate in vivo steroidogenesis in a diseased state. This modelling approach was applied to the South African Angora goat, that suffers from hypocortisolism caused by altered adrenal function. These animals are extremely vulnerable to cold stress, leading to substantial monetary loss in the mohair industry. The Angora goat has increased CYP17A1 17,20-lyase enzyme activity in comparison with hardy livestock species. Determining the effect of this altered adrenal function on adrenal steroidogenesis during a cold stress response is difficult. We developed a model describing adrenal steroidogenesis under control conditions, and under altered steroidogenic conditions where the animal suffers from hypocortisolism. The model is parameterised with experimental data from in vitro enzyme characterisations of a hardy control species. The increased 17,20-lyase activity of the Angora goat CYP17A1 enzyme was subsequently incorporated into the model and the response to physiological stress is simulated under both control and altered adrenal steroidogenic conditions., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Many organs have internal structures with spatially differentiated and sometimes temporally synchronized groups of cells. The mechanisms leading to such differentiation and coordination are not well understood. Here we design a diffusion-limited microfluidic system to mimic a multicellular organ structure with peripheral blood flow and test whether a group of individually oscillating yeast cells could form subpopulations of spatially differentiated and temporally synchronized cells. Upon substrate addition, the dynamic response at single-cell level shows glycolytic oscillations, leading to wave fronts traveling through the monolayered population and to synchronized communities at well-defined positions in the cell chamber. A detailed mechanistic model with the architectural structure of the flow chamber incorporated successfully predicts the spatial-temporal experimental data, and allows for a molecular understanding of the observed phenomena. The intricate interplay of intracellular biochemical reaction networks leading to the oscillations, combined with intercellular communication via metabolic intermediates and fluid dynamics of the reaction chamber, is responsible for the generation of the subpopulations of synchronized cells. This mechanism, as analyzed from the model simulations, is experimentally tested using different concentrations of cyanide stress solutions. The results are reproducible and stable, despite cellular heterogeneity, and the spontaneous community development is reminiscent of a zoned cell differentiation often observed in multicellular organs., Competing Interests: The authors declare no competing interest., (Copyright © 2021 the Author(s). Published by PNAS.)

Aims: A mathematical model of the nonribosomal synthesis of tyrocidines and analogues by Brevibacillus parabrevis was constructed using a competitive binding mechanism (CBM) for the incorporation of the three variable aromatic amino acid (Aaa) residues in their sequence. These antimicrobial peptides have a conserved structure (D-Phe 1 -Pro 2 -Aaa 3 -D-Aaa 4 -Asn 5 -Gln 6 -Aaa 7 -Val 8 -Orn 9 -Leu 10 ), apart from the Aaa in positions 3, 4 and 7 containing either Phe, Trp or Tyr., Methods and Results: Ultra-performance liquid chromatography linked mass spectrometry was used to profile peptides from extracts of cultures grown in media with various Phe : Trp ratios. The CBM model describes the production of peptides as a function of growth medium Aaa concentration. The model accounts for variable Aaa incorporation by simultaneously considering the influence of maximal incorporation rate and cooperativity, despite similar K M' s of synthetase modules., Conclusions: Our CBM model can be utilized to predict the Aaa composition of produced peptides from the concentration of Aaas in the growth medium., Significance and Impact of the Study: Subtly exploiting the inherent promiscuity of the nontemplate coded peptide synthesis allows for external control of peptide identity, without using genetic manipulation. Such versatility is exploitable in the production of targeted peptide complexes and rare peptides where production processes are reliant on nonribosomal synthesis., (© 2019 The Society for Applied Microbiology.)

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation., (© The Author(s) 2018. Published by Oxford University Press.)

In this unit, we provide a clear exposition of the methodology employed to study dynamic responses in individual cells, using microfluidics for controlling and adjusting the cell environment, optical tweezers for precise cell positioning, and fluorescence microscopy for detecting intracellular responses. This unit focuses on the induction and study of glycolytic oscillations in single yeast cells, but the methodology can easily be adjusted to examine other biological questions and cell types. We present a step-by-step guide for fabrication of the microfluidic device, for alignment of the optical tweezers, for cell preparation, and for time-lapse imaging of glycolytic oscillations in single cells, including a discussion of common pitfalls. A user who follows the protocols should be able to detect clear metabolite time traces over the course of up to an hour that are indicative of dynamics on the second scale in individual cells during fast and reversible environmental adjustments. © 2018 by John Wiley & Sons, Inc., (© 2018 John Wiley & Sons, Inc.)

The response of oscillatory systems to external perturbations is crucial for emergent properties such as synchronisation and phase locking and can be quantified in a phase response curve (PRC). In individual, oscillating yeast cells, we characterised experimentally the phase response of glycolytic oscillations for external acetaldehyde pulses and followed the transduction of the perturbation through the system. Subsequently, we analysed the control of the relevant system components in a detailed mechanistic model. The observed responses are interpreted in terms of the functional coupling and regulation in the reaction network. We find that our model quantitatively predicts the phase-dependent phase shift observed in the experimental data. The phase shift is in agreement with an adaptation leading to synchronisation with an external signal. Our model analysis establishes that phosphofructokinase plays a key role in the phase shift dynamics as shown in the PRC and adaptation time to external perturbations. Specific mechanism-based interventions, made possible through such analyses of detailed models, can improve upon standard trial and error methods, e.g. melatonin supplementation to overcome jet-lag, which are error-prone, specifically, since the effects are phase dependent and dose dependent. The models by Gustavsson and Goldbeter discussed in the text can be obtained from the JWS Online simulation database: (https://jjj.bio.vu.nl/models/gustavsson5 and https://jjj.bio.vu.nl/models/goldbeter1)., (© 2019 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.)

The progression of castration resistant prostate cancer (CRPC) is driven by the intratumoral conversion of adrenal androgen precursors to potent androgens. The expression of aldo-keto reductase 1C3 (AKR1C3), which catalyses the reduction of weak androgens to more potent androgens, is significantly increased in CRPC tumours. The oxidation of androgens to their inactive form is catalysed by 17β-hydroxysteroid dehydrogenase type 2 (17βHSD2), but little attention is given to the expression levels of this enzyme. In this study, we show that the 11-oxygenated androgen precursors of adrenal origin are the preferred substrate for AKR1C3. In particular we show that the enzymatic efficiency of AKR1C3 is 8- and 24-fold greater for 11-ketoandrostenedione than for the classic substrates androstenedione and 5α-androstanedione, respectively. Using three independent experimental systems and a computational model we subsequently show that increased ratios of AKR1C3:17βHSD2 significantly favours the flux through the 11-oxygenated androgen pathway as compared to the classical or 5α-androstanedione pathways. Our findings reveal that the flux through the classical and 5α-androstanedione pathways are limited by the low catalytic efficiently of AKR1C3 towards classical androgens combined with the high catalytic efficiency of 17βHSD2, and that the expression of the oxidative enzyme therefore plays a vital role in determining the steady state concentration of active androgens. Using microarray data from prostate tissue we confirm that the AKR1C3:17βHSD2 ratio is significantly increased in patients undergoing androgen deprivation therapy as compared to benign tissue, and further increased in patients with CRPC. Taken together this study therefore demonstrates that the ratio of AKR1C3:17βHSD2 is more important than AKR1C3 expression alone in determining intratumoral androgen levels and that 11-oxygenated androgens may play a bigger role in CRPC than previously anticipated., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

In (hyper)thermophilic organisms metabolic processes have to be adapted to function optimally at high temperature. We compared the gluconeogenic conversion of 3-phosphoglycerate via 1,3-bisphosphoglycerate to glyceraldehyde-3-phosphate at 30 °C and at 70 °C. At 30 °C it was possible to produce 1,3-bisphosphoglycerate from 3-phosphoglycerate with phosphoglycerate kinase, but at 70 °C, 1,3-bisphosphoglycerate was dephosphorylated rapidly to 3-phosphoglycerate, effectively turning the phosphoglycerate kinase into a futile cycle. When phosphoglycerate kinase was incubated together with glyceraldehyde 3-phosphate dehydrogenase it was possible to convert 3-phosphoglycerate to glyceraldehyde 3-phosphate, both at 30 °C and at 70 °C, however, at 70 °C only low concentrations of product were observed due to thermal instability of glyceraldehyde 3-phosphate. Thus, thermolabile intermediates challenge central metabolic reactions and require special adaptation strategies for life at high temperature.

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

Summary: JWS Online is a web-based platform for construction, simulation and exchange of models in standard formats. We have extended the platform with a database for curated simulation experiments that can be accessed directly via a URL, allowing one-click reproduction of published results. Users can modify the simulation experiments and export them in standard formats. The Simulation database thus lowers the bar on exploring computational models, helps users create valid simulation descriptions and improves the reproducibility of published simulation experiments., Availability and Implementation: The Simulation Database is available on line at https://jjj.bio.vu.nl/models/experiments/ ., Contact: jls@sun.ac.za ., (© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com)

Mathematical models are key to systems biology where they typically describe the topology and dynamics of biological networks, listing biochemical entities and their relationships with one another. Some (hyper)thermophilic Archaea contain an enzyme, called non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase (GAPN), which catalyzes the direct oxidation of glyceraldehyde-3-phosphate to 3-phosphoglycerate omitting adenosine 5'-triphosphate (ATP) formation by substrate-level-phosphorylation via phosphoglycerate kinase. In this study we formulate three hypotheses that could explain functionally why GAPN exists in these Archaea, and then construct and use mathematical models to test these three hypotheses. We used kinetic parameters of enzymes of Sulfolobus solfataricus ( S. solfataricus ) which is a thermo-acidophilic archaeon that grows optimally between 60 and 90 °C and between pH 2 and 4. For comparison, we used a model of Saccharomyces cerevisiae ( S. cerevisiae ), an organism that can live at moderate temperatures. We find that both the first hypothesis, i.e., that the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) plus phosphoglycerate kinase (PGK) route (the alternative to GAPN) is thermodynamically too much uphill and the third hypothesis, i.e., that GAPDH plus PGK are required to carry the flux in the gluconeogenic direction, are correct. The second hypothesis, i.e., that the GAPDH plus PGK route delivers less than the 1 ATP per pyruvate that is delivered by the GAPN route, is only correct when GAPDH reaction has a high rate and 1,3- bis -phosphoglycerate (BPG) spontaneously degrades to 3PG at a high rate.

The development of drugs that can inactivate disease-causing cells (e.g. cancer cells or parasites) without causing collateral damage to healthy or to host cells is complicated by the fact that many proteins are very similar between organisms. Nevertheless, due to subtle, quantitative differences between the biochemical reaction networks of target cell and host, a drug can limit the flux of the same essential process in one organism more than in another. We identified precise criteria for this 'network-based' drug selectivity, which can serve as an alternative or additive to structural differences. We combined computational and experimental approaches to compare energy metabolism in the causative agent of sleeping sickness, Trypanosoma brucei, with that of human erythrocytes, and identified glucose transport and glyceraldehyde-3-phosphate dehydrogenase as the most selective antiparasitic targets. Computational predictions were validated experimentally in a novel parasite-erythrocytes co-culture system. Glucose-transport inhibitors killed trypanosomes without killing erythrocytes, neurons or liver cells.

The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models (https://fairdomhub.org/) for the Systems Biology community. It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship., (© The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Progestins used in contraception and hormone replacement therapy are synthetic compounds designed to mimic the actions of the natural hormone progesterone and are classed into four consecutive generations. The biological actions of progestins are primarily determined by their interactions with steroid receptors, and factors such as metabolism, pharmacokinetics, bioavailability and the regulation of endogenous steroid hormone biosynthesis are often overlooked. Although some studies have investigated the effects of select progestins on a few steroidogenic enzymes, studies comparing the effects of progestins from different generations are lacking. This study therefore explored the putative modulatory effects of progestins on de novo steroid synthesis in the adrenal by comparing the effects of select progestins from the respective generations, on endogenous steroid hormone production by the H295R human adrenocortical carcinoma cell line. Ultra-performance liquid chromatography/tandem mass spectrometry analysis showed that the fourth-generation progestins, nestorone (NES), nomegestrol acetate (NoMAC) and drospirenone (DRSP), unlike the progestins selected from the first three generations, modulate the biosynthesis of several endogenous steroids. Subsequent assays performed in COS-1 cells expressing human 3βHSD2, suggest that these progestins modulate the biosynthesis of steroid hormones by inhibiting the activity of 3βHSD2. The Ki values determined for the inhibition of human 3βHSD2 by NES (9.5 ± 0.96 nM), NoMAC (29 ± 7.1 nM) and DRSP (232 ± 38 nM) were within the reported concentration ranges for the contraceptive use of these progestins in vivo. Taken together, our results suggest that newer, fourth-generation progestins may exert both positive and negative physiological effects via the modulation of endogenous steroid hormone biosynthesis., Competing Interests: The authors have declared that no competing interests exist.

Bioinformatics is now a critical skill in many research and commercial environments as biological data are increasing in both size and complexity. South African researchers recognized this need in the mid-1990s and responded by working with the government as well as international bodies to develop initiatives to build bioinformatics capacity in the country. Significant injections of support from these bodies provided a springboard for the establishment of computational biology units at multiple universities throughout the country, which took on teaching, basic research and support roles. Several challenges were encountered, for example with unreliability of funding, lack of skills, and lack of infrastructure. However, the bioinformatics community worked together to overcome these, and South Africa is now arguably the leading country in bioinformatics on the African continent. Here we discuss how the discipline developed in the country, highlighting the challenges, successes, and lessons learnt.

Unlabelled: Glycolysis is the main pathway for ATP production in the malaria parasite Plasmodium falciparum and essential for its survival. Following a sensitivity analysis of a detailed kinetic model for glycolysis in the parasite, the glucose transport reaction was identified as the step whose activity needed to be inhibited to the least extent to result in a 50% reduction in glycolytic flux. In a subsequent inhibitor titration with cytochalasin B, we confirmed the model analysis experimentally and measured a flux control coefficient of 0.3 for the glucose transporter. In addition to the glucose transporter, the glucokinase and phosphofructokinase had high flux control coefficients, while for the ATPase a small negative flux control coefficient was predicted. In a broader comparative analysis of glycolytic models, we identified a weakness in the P. falciparum pathway design with respect to stability towards perturbations in the ATP demand., Database: The mathematical model described here has been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.bio.vu.nl/database/vanniekerk1. The SEEK-study including the experimental data set is available at DOI 10.15490/seek.1., Investigation: 56 (http://dx.doi.org/10.15490/seek.1., Investigation: 56)., (© 2015 FEBS.)

We propose a hierarchical modelling approach to construct models for disease states at the whole-body level. Such models can simulate effects of drug-induced inhibition of reaction steps on the whole-body physiology. We illustrate the approach for glucose metabolism in malaria patients, by merging two detailed kinetic models for glucose metabolism in the parasite Plasmodium falciparum and the human red blood cell with a coarse-grained model for whole-body glucose metabolism. In addition we use a genome-scale metabolic model for the parasite to predict amino acid production profiles by the malaria parasite that can be used as a complex biomarker., (© 2015 Authors; published by Portland Press Limited.)

Background: Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them., Results: The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data., Conclusion: The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and features of the SEEK software, and describes the use of the SEEK in the SysMO consortium (Systems biology for Micro-organisms), and the VLN (virtual Liver Network), two large systems biology initiatives with different research aims and different scientific communities.

Unlabelled: The enzymes in the Embden-Meyerhof-Parnas pathway of Plasmodium falciparum trophozoites were kinetically characterized and their integrated activities analyzed in a mathematical model. For validation of the model, we compared model predictions for steady-state fluxes and metabolite concentrations of the hexose phosphates with experimental values for intact parasites. The model, which is completely based on kinetic parameters that were measured for the individual enzymes, gives an accurate prediction of the steady-state fluxes and intermediate concentrations. This is the first detailed kinetic model for glucose metabolism in P. falciparum, one of the most prolific malaria-causing protozoa, and the high predictive power of the model makes it a strong tool for future drug target identification studies. The modelling workflow is transparent and reproducible, and completely documented in the SEEK platform, where all experimental data and model files are available for download., Database: The mathematical models described in the present study have been submitted to the JWS Online Cellular Systems Modelling Database (http://jjj.bio.vu.nl/database/penkler). The investigation and complete experimental data set is available on SEEK (10.15490/seek.1., Investigation: 56)., (© 2015 FEBS.)

N-substituted pantothenamides are analogues of pantothenic acid, the vitamin precursor of CoA, and constitute a class of well-studied bacterial growth inhibitors that show potential as new antibacterial agents. Previous studies have highlighted the importance of pantothenate kinase (PanK; EC 2.7.1.33) (the first enzyme of CoA biosynthesis) in mediating pantothenamide-induced growth inhibition by one of two proposed mechanisms: first, by acting on the pantothenamides as alternate substrates (allowing their conversion into CoA antimetabolites, with subsequent effects on CoA- and acyl carrier protein-dependent processes) or, second, by being directly inhibited by them (causing a reduction in CoA biosynthesis). In the present study we used structurally modified pantothenamides to probe whether PanKs interact with these compounds in the same manner. We show that the three distinct types of eubacterial PanKs that are known to exist (PanKI , PanKII and PanKIII ) respond very differently and, consequently, are responsible for determining the pantothenamide mode of action in each case: although the promiscuous PanKI enzymes accept them as substrates, the highly selective PanKIII s are resistant to their inhibitory effects. Most unexpectedly, Staphylococcus aureus PanK (the only known example of a bacterial PanKII ) experiences uncompetitive inhibition in a manner that is described for the first time. In addition, we show that pantetheine, a CoA degradation product that closely resembles the pantothenamides, causes the same effect. This suggests that, in S. aureus, pantothenamides may act by usurping a previously unknown role of pantetheine in the regulation of CoA biosynthesis, and validates its PanK as a target for the development of new antistaphylococcal agents., (© 2014 FEBS.)

Unlabelled: Oscillations are widely distributed in nature and synchronization of oscillators has been described at the cellular level (e.g. heart cells) and at the population level (e.g. fireflies). Yeast glycolysis is the best known oscillatory system, although it has been studied almost exclusively at the population level (i.e. limited to observations of average behaviour in synchronized cultures). We studied individual yeast cells that were positioned with optical tweezers in a microfluidic chamber to determine the precise conditions for autonomous glycolytic oscillations. Hopf bifurcation points were determined experimentally in individual cells as a function of glucose and cyanide concentrations. The experiments were analyzed in a detailed mathematical model and could be interpreted in terms of an oscillatory manifold in a three-dimensional state-space; crossing the boundaries of the manifold coincides with the onset of oscillations and positioning along the longitudinal axis of the volume sets the period. The oscillatory manifold could be approximated by allosteric control values of phosphofructokinase for ATP and AMP., Database: The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.mib.ac.uk/webMathematica/UItester.jsp?modelName=gustavsson5. [Database section added 14 May 2014 after original online publication]., (© 2014 FEBS.)

There are many examples of oscillations in biological systems and one of the most investigated is glycolytic oscillations in yeast. These oscillations have been studied since the 1950s in dense, synchronized populations and in cell-free extracts, but it has for long been unknown whether a high cell density is a requirement for oscillations to be induced, or if individual cells can oscillate also in isolation without synchronization. Here we present an experimental method and a detailed kinetic model for studying glycolytic oscillations in individual, isolated yeast cells and compare them to previously reported studies of single-cell oscillations. The importance of single-cell studies of this phenomenon and relevant future research questions are also discussed., (Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.)

Background: Glutathione metabolism can determine an individual's ability to detoxify drugs. To increase understanding of the dynamics of cellular glutathione homeostasis, we have developed an experiment-based mathematical model of the kinetics of the glutathione network. This model was used to simulate perturbations observed when human liver derived THLE cells, transfected with human cytochrome P452E1 (THLE-2E1 cells), were exposed to paracetamol (acetaminophen)., Methods: Human liver derived cells containing extra human cytochrome P4502E1 were treated with paracetamol at various levels of methionine and in the presence and absence of an inhibitor of glutamyl-cysteine synthetase (GCS). GCS activity was also measured in extracts. Intracellular and extracellular concentrations of substances involved in glutathione metabolism were measured as was damage to mitochondria and proteins. A bottom up mathematical model was made of the metabolic pathways around and including glutathione., Results: Our initial model described some, but not all the metabolite-concentration and flux data obtained when THLE-2E1 cells were exposed to paracetamol at concentrations high enough to affect glutathione metabolism. We hypothesized that the lack of correspondence could be due to upregulation of expression of glutamyl cysteine synthetase, one of the enzymes controlling glutathione synthesis, and confirmed this experimentally. A modified model which incorporated this adaptive response adequately described the observed changes in the glutathione pathway. Use of the adaptive model to analyze the functioning of the glutathione network revealed that a threshold input concentration of methionine may be required for effective detoxification of reactive metabolites by glutathione conjugation. The analysis also provided evidence that 5-oxoproline and ophthalmic acid are more useful biomarkers of glutathione status when analyzed together than when analyzed in isolation, especially in a new, model-assisted integrated biomarker strategy., Conclusion: A robust mathematical model of the dynamics of cellular changes in glutathione homeostasis in cells has been developed and tested in vitro., General Significance: Mathematical models of the glutathione pathway that help examine mechanisms of cellular protection against xenobiotic toxicity and the monitoring thereof, can now be made., (Copyright © 2013 Elsevier B.V. All rights reserved.)

Four enzymes of the gluconeogenic pathway in Sulfolobus solfataricus were purified and kinetically characterized. The enzymes were reconstituted in vitro to quantify the contribution of temperature instability of the pathway intermediates to carbon loss from the system. The reconstituted system, consisting of phosphoglycerate kinase, glyceraldehyde 3-phosphate dehydrogenase, triose phosphate isomerase and the fructose 1,6-bisphosphate aldolase/phosphatase, maintained a constant consumption rate of 3-phosphoglycerate and production of fructose 6-phosphate over a 1-h period. Cofactors ATP and NADPH were regenerated via pyruvate kinase and glucose dehydrogenase. A mathematical model was constructed on the basis of the kinetics of the purified enzymes and the measured half-life times of the pathway intermediates. The model quantitatively predicted the system fluxes and metabolite concentrations. Relative enzyme concentrations were chosen such that half the carbon in the system was lost due to degradation of the thermolabile intermediates dihydroxyacetone phosphate, glyceraldehyde 3-phosphate and 1,3-bisphosphoglycerate, indicating that intermediate instability at high temperature can significantly affect pathway efficiency., (© 2013 FEBS.)

Selective robustness is a key feature of biochemical networks. It confers a fitness benefit to organisms living in dynamic environments. The (in-)sensitivity of a network to external perturbations results from the interplay between network dynamics, structure and enzyme kinetics. In this work, we focus on the subtle interplay between robustness and control (fragility). We describe a quantitative method for defining the fragility and robustness of system fluxes to perturbations. We find that for many mathematical models of metabolic pathways, the robustness of fluxes vis-à-vis perturbations of all the enzyme activities is captured by a broad distribution of the robustness coefficients. We find that in cases where a metabolic pathway flux is made less robust with respect to the perturbation of a particular network step, the average robustness may still be increased. We then show that fragility is conserved upon a perturbation of network processes and equate fragility with control as defined in metabolic control analysis. This highlights the non-intuitive nature of the interplay between fragility and robustness and the need for a dynamic network understanding., (© 2012 The Authors Journal compilation © 2012 FEBS.)

Enzyme kinetics for systems biology should ideally yield information about the enzyme's activity under in vivo conditions, including such reaction features as substrate cooperativity, reversibility and allostery, and be applicable to enzymatic reactions with multiple substrates. A large body of enzyme-kinetic data in the literature is based on the uni-substrate Michaelis-Menten equation, which makes unnatural assumptions about enzymatic reactions (e.g., irreversibility), and its application in systems biology models is therefore limited. To overcome this limitation, we have utilised NMR time-course data in a combined theoretical and experimental approach to parameterize the generic reversible Hill equation, which is capable of describing enzymatic reactions in terms of all the properties mentioned above and has fewer parameters than detailed mechanistic kinetic equations; these parameters are moreover defined operationally. Traditionally, enzyme kinetic data have been obtained from initial-rate studies, often using assays coupled to NAD(P)H-producing or NAD(P)H-consuming reactions. However, these assays are very labour-intensive, especially for detailed characterisation of multi-substrate reactions. We here present a cost-effective and relatively rapid method for obtaining enzyme-kinetic parameters from metabolite time-course data generated using NMR spectroscopy. The method requires fewer runs than traditional initial-rate studies and yields more information per experiment, as whole time-courses are analyzed and used for parameter fitting. Additionally, this approach allows real-time simultaneous quantification of all metabolites present in the assay system (including products and allosteric modifiers), which demonstrates the superiority of NMR over traditional spectrophotometric coupled enzyme assays. The methodology presented is applied to the elucidation of kinetic parameters for two coupled glycolytic enzymes from Escherichia coli (phosphoglucose isomerase and phosphofructokinase). 31P-NMR time-course data were collected by incubating cell extracts with substrates, products and modifiers at different initial concentrations. NMR kinetic data were subsequently processed using a custom software module written in the Python programming language, and globally fitted to appropriately modified Hill equations.

Unlabelled: An existing detailed kinetic model for the steady-state behavior of yeast glycolysis was tested for its ability to simulate dynamic behavior. Using a small subset of experimental data, the original model was adapted by adjusting its parameter values in three optimization steps. Only small adaptations to the original model were required for realistic simulation of experimental data for limit-cycle oscillations. The greatest changes were required for parameter values for the phosphofructokinase reaction. The importance of ATP for the oscillatory mechanism and NAD(H) for inter-and intra-cellular communications and synchronization was evident in the optimization steps and simulation experiments. In an accompanying paper [du Preez F et al. (2012) FEBS J279, 2823-2836], we validate the model for a wide variety of experiments on oscillatory yeast cells. The results are important for re-use of detailed kinetic models in modular modeling approaches and for approaches such as that used in the Silicon Cell initiative., Database: The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/dupreez/index.html., (© 2012 The Authors Journal compilation © 2012 FEBS.)

An important goal of toxicology is to understand and predict the adverse effects of drugs and other xenobiotics. For pharmaceuticals, such effects often emerge unexpectedly in man even when absent from trials in vitro and in animals. Although drugs and xenobiotics act on molecules, it is their perturbation of intracellular networks that matters. The tremendous complexity of these networks makes it difficult to understand the effects of xenobiotics on their ability to function. Because systems biology integrates data concerning molecules and their interactions into an understanding of network behaviour, it should be able to assist toxicology in this respect. This review identifies how in silico systems biology tools, such as kinetic modelling, and metabolic control, robustness and flux analyse, may indeed help understanding network-mediated toxicity. It also shows how these approaches function by implementing them vis-à-vis the glutathione network, which is important for the detoxification of reactive drug metabolites. The tools enable the appreciation of the steady state concept for the detoxification network and make it possible to simulate and then understand effects of perturbations of the macromolecules in the pathway that are counterintuitive. We review how a glutathione model has been used to explain the impact of perturbation of the pathway at various molecular sites, as would be the effect of single-nucleotide polymorphisms. We focus on how the mutations impact the levels of glutathione and of two candidate biomarkers of hepatic glutathione status. We conclude this review by sketching how the various systems biology tools may help in the various phases of drug development in the pharmaceutical industry.

Unlabelled: In an accompanying paper [du Preez et al., (2012) FEBS J279, 2810-2822], we adapt an existing kinetic model for steady-state yeast glycolysis to simulate limit-cycle oscillations. Here we validate the model by testing its capacity to simulate a wide range of experiments on dynamics of yeast glycolysis. In addition to its description of the oscillations of glycolytic intermediates in intact cells and the rapid synchronization observed when mixing out-of-phase oscillatory cell populations (see accompanying paper), the model was able to predict the Hopf bifurcation diagram with glucose as the bifurcation parameter (and one of the bifurcation points with cyanide as the bifurcation parameter), the glucose- and acetaldehyde-driven forced oscillations, glucose and acetaldehyde quenching, and cell-free extract oscillations (including complex oscillations and mixed-mode oscillations). Thus, the model was compliant, at least qualitatively, with the majority of available experimental data for glycolytic oscillations in yeast. To our knowledge, this is the first time that a model for yeast glycolysis has been tested against such a wide variety of independent data sets., Database: The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/dupreez/index.html., (© 2012 The Authors Journal compilation © 2012 FEBS.)

Unlabelled: Yeast glycolytic oscillations have been studied since the 1950s in cell-free extracts and intact cells. For intact cells, sustained oscillations have so far only been observed at the population level, i.e. for synchronized cultures at high biomass concentrations. Using optical tweezers to position yeast cells in a microfluidic chamber, we were able to observe sustained oscillations in individual isolated cells. Using a detailed kinetic model for the cellular reactions, we simulated the heterogeneity in the response of the individual cells, assuming small differences in a single internal parameter. This is the first time that sustained limit-cycle oscillations have been demonstrated in isolated yeast cells., Database: The mathematical model described here has been submitted to the JWS Online Cellular Systems Modelling Database and can be accessed at http://jjj.biochem.sun.ac.za/database/gustavsson/index.html free of charge., (© 2012 The Authors Journal compilation © 2012 FEBS.)

The development of disease may be characterized as a pathological shift of homeostasis; the main goal of contemporary drug treatment is, therefore, to return the pathological homeostasis back to the normal physiological range. From the view point of systems biology, homeostasis emerges from the interactions within the network of biomolecules (e.g. DNA, mRNA, proteins), and, hence, understanding how drugs impact upon the entire network should improve their efficacy at returning the network (body) to physiological homeostasis. Large, mechanism-based computer models, such as the anticipated human whole body models (silicon or virtual human), may help in the development of such network-targeting drugs. Using the philosophical concept of weak and strong emergence, we shall here take a more general look at the paradigm of network-targeting drugs, and propose our approaches to scale the strength of strong emergence. We apply these approaches to several biological examples and demonstrate their utility to reveal principles of bio-modeling. We discuss this in the perspective of building the silicon human., (Crown Copyright © 2011. Published by Elsevier B.V. All rights reserved.)

One of the main pathways for the detoxification of reactive metabolites in the liver involves glutathione conjugation. Metabolic profiling studies have shown paradoxical responses in glutathione-related biochemical pathways. One of these is the increase in 5-oxoproline and ophthalmic acid concentrations with increased dosage of paracetamol. Experimental studies have thus far failed to resolve these paradoxes and the robustness of how these proposed biomarkers correlate with liver glutathione levels has been questioned. To better understand how these biomarkers behave in the glutathione system a kinetic model of this pathway was made. By using metabolic control analysis and by simulating biomarker levels under a variety of conditions, we found that 5-oxoproline and ophthalmic acid concentrations may not only depend on the glutathione but also on the methionine status of the cell. We show that neither of the two potential biomarkers are reliable on their own since they need additional information about the methionine status of the system to relate them uniquely to intracellular glutathione concentration. However, when both biomarkers are measured simultaneously a direct inference of the glutathione concentration can be made, irrespective of the methionine concentration in the system., (Copyright © 2011 Elsevier B.V. All rights reserved.)